Compare commits
1 Commits
| Author | SHA1 | Date |
|---|---|---|
karljiang118440
|
260fe77ad0 |
90
backend/.env
90
backend/.env
|
|
@ -1,90 +0,0 @@
|
|||
# ========================================
|
||||
# 大模型配置 (支持OpenAI协议的第三方服务)
|
||||
# ========================================
|
||||
# 可选择的提供商: openai, deepseek, doubao, zhipu, moonshot
|
||||
LLM_PROVIDER=doubao
|
||||
|
||||
# Embedding模型配置
|
||||
# 可选择的提供商: openai, deepseek, doubao, zhipu, moonshot
|
||||
EMBEDDING_PROVIDER=zhipu
|
||||
|
||||
# OpenAI配置
|
||||
OPENAI_API_KEY=your-openai-api-key
|
||||
OPENAI_BASE_URL=https://api.openai.com/v1
|
||||
OPENAI_MODEL=gpt-3.5-turbo
|
||||
|
||||
# DeepSeek配置
|
||||
DEEPSEEK_API_KEY=your-deepseek-api-key
|
||||
DEEPSEEK_BASE_URL=https://api.deepseek.com/v1
|
||||
DEEPSEEK_MODEL=deepseek-chat
|
||||
|
||||
# 豆包(字节跳动)配置
|
||||
DOUBAO_API_KEY=your-doubao-api-key
|
||||
DOUBAO_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
|
||||
DOUBAO_MODEL=doubao-1-5-pro-32k-250115
|
||||
|
||||
# 智谱AI配置
|
||||
ZHIPU_API_KEY=your-zhipu-api-key
|
||||
ZHIPU_BASE_URL=https://open.bigmodel.cn/api/paas/v4
|
||||
ZHIPU_MODEL=glm-4
|
||||
ZHIPU_EMBEDDING_MODEL=embedding-3
|
||||
|
||||
# 月之暗面配置
|
||||
MOONSHOT_API_KEY=your-moonshot-api-key
|
||||
MOONSHOT_BASE_URL=https://api.moonshot.cn/v1
|
||||
MOONSHOT_MODEL=moonshot-v1-8k
|
||||
MOONSHOT_EMBEDDING_MODEL=moonshot-embedding
|
||||
|
||||
# Embedding模型配置
|
||||
OPENAI_EMBEDDING_MODEL=text-embedding-ada-002
|
||||
DEEPSEEK_EMBEDDING_MODEL=deepseek-embedding
|
||||
DOUBAO_EMBEDDING_MODEL=doubao-embedding
|
||||
|
||||
# 工具API配置
|
||||
## tavilySearch api
|
||||
TAVILY_API_KEY=your-tavily-api-key
|
||||
## 心知天气api
|
||||
WEATHER_API_KEY=your_xinzhi_api_key
|
||||
|
||||
# ========================================
|
||||
# 应用配置
|
||||
# ========================================
|
||||
# 后端应用配置
|
||||
APP_NAME=TH-Agenter
|
||||
APP_VERSION=0.1.0
|
||||
DEBUG=true
|
||||
ENVIRONMENT=development
|
||||
HOST=0.0.0.0
|
||||
PORT=8000
|
||||
|
||||
# 前端应用配置
|
||||
VITE_API_BASE_URL=http://localhost:8000/api
|
||||
VITE_APP_TITLE=TH-Agenter
|
||||
VITE_APP_VERSION=1.0.0
|
||||
VITE_ENABLE_MOCK=false
|
||||
VITE_UPLOAD_MAX_SIZE=10485760
|
||||
VITE_SUPPORTED_FILE_TYPES=pdf,txt,md,doc,docx,ppt,pptx,xls,xlsx
|
||||
|
||||
# ========================================
|
||||
# 安全配置
|
||||
# ========================================
|
||||
SECRET_KEY=your-secret-key-here-change-in-production
|
||||
ALGORITHM=HS256
|
||||
ACCESS_TOKEN_EXPIRE_MINUTES=300
|
||||
|
||||
# ========================================
|
||||
# 数据库配置
|
||||
# ========================================
|
||||
# 数据库URL配置
|
||||
DATABASE_URL=sqlite:///./TH-Agenter.db
|
||||
# DATABASE_URL=postgresql://iagent:iagent@118.196.30.45:5432/iagent
|
||||
|
||||
# ========================================
|
||||
# 向量数据库配置
|
||||
# ========================================
|
||||
VECTOR_DB_TYPE=pgvector
|
||||
PGVECTOR_HOST=118.196.30.45
|
||||
PGVECTOR_PORT=5432
|
||||
PGVECTOR_DATABASE=iagent
|
||||
PGVECTOR_USER=iagent
|
||||
PGVECTOR_PASSWORD=iagent
|
||||
|
|
@ -1,89 +0,0 @@
|
|||
# ========================================
|
||||
# 大模型配置 (支持OpenAI协议的第三方服务)
|
||||
# ========================================
|
||||
# 可选择的提供商: openai, deepseek, doubao, zhipu, moonshot
|
||||
LLM_PROVIDER=doubao
|
||||
|
||||
# Embedding模型配置
|
||||
# 可选择的提供商: openai, deepseek, doubao, zhipu, moonshot
|
||||
EMBEDDING_PROVIDER=zhipu
|
||||
|
||||
# OpenAI配置
|
||||
OPENAI_API_KEY=your-openai-api-key
|
||||
OPENAI_BASE_URL=https://api.openai.com/v1
|
||||
OPENAI_MODEL=gpt-3.5-turbo
|
||||
|
||||
# DeepSeek配置
|
||||
DEEPSEEK_API_KEY=your-deepseek-api-key
|
||||
DEEPSEEK_BASE_URL=https://api.deepseek.com/v1
|
||||
DEEPSEEK_MODEL=deepseek-chat
|
||||
|
||||
# 豆包(字节跳动)配置
|
||||
DOUBAO_API_KEY=your-doubao-api-key
|
||||
DOUBAO_BASE_URL=https://ark.cn-beijing.volces.com/api/v3
|
||||
DOUBAO_MODEL=doubao-1-5-pro-32k-250115
|
||||
|
||||
# 智谱AI配置
|
||||
ZHIPU_API_KEY=your-zhipu-api-key
|
||||
ZHIPU_BASE_URL=https://open.bigmodel.cn/api/paas/v4
|
||||
ZHIPU_MODEL=glm-4
|
||||
ZHIPU_EMBEDDING_MODEL=embedding-3
|
||||
|
||||
# 月之暗面配置
|
||||
MOONSHOT_API_KEY=your-moonshot-api-key
|
||||
MOONSHOT_BASE_URL=https://api.moonshot.cn/v1
|
||||
MOONSHOT_MODEL=moonshot-v1-8k
|
||||
MOONSHOT_EMBEDDING_MODEL=moonshot-embedding
|
||||
|
||||
# Embedding模型配置
|
||||
OPENAI_EMBEDDING_MODEL=text-embedding-ada-002
|
||||
DEEPSEEK_EMBEDDING_MODEL=deepseek-embedding
|
||||
DOUBAO_EMBEDDING_MODEL=doubao-embedding
|
||||
|
||||
# 工具API配置
|
||||
## tavilySearch api
|
||||
TAVILY_API_KEY=your-tavily-api-key
|
||||
## 心知天气api
|
||||
WEATHER_API_KEY=your_xinzhi_api_key
|
||||
|
||||
# ========================================
|
||||
# 应用配置
|
||||
# ========================================
|
||||
# 后端应用配置
|
||||
APP_NAME=TH-Agenter
|
||||
APP_VERSION=0.1.0
|
||||
DEBUG=true
|
||||
ENVIRONMENT=development
|
||||
HOST=0.0.0.0
|
||||
PORT=8000
|
||||
|
||||
# 前端应用配置
|
||||
VITE_API_BASE_URL=http://localhost:8000/api
|
||||
VITE_APP_TITLE=TH-Agenter
|
||||
VITE_APP_VERSION=1.0.0
|
||||
VITE_ENABLE_MOCK=false
|
||||
VITE_UPLOAD_MAX_SIZE=10485760
|
||||
VITE_SUPPORTED_FILE_TYPES=pdf,txt,md,doc,docx,ppt,pptx,xls,xlsx
|
||||
|
||||
# ========================================
|
||||
# 安全配置
|
||||
# ========================================
|
||||
SECRET_KEY=your-secret-key-here-change-in-production
|
||||
ALGORITHM=HS256
|
||||
ACCESS_TOKEN_EXPIRE_MINUTES=300
|
||||
|
||||
# ========================================
|
||||
# 数据库配置
|
||||
# ========================================
|
||||
|
||||
DATABASE_URL=postgresql://iagent:iagent@118.196.30.45:5432/iagent
|
||||
|
||||
# ========================================
|
||||
# 向量数据库配置
|
||||
# ========================================
|
||||
VECTOR_DB_TYPE=pgvector
|
||||
PGVECTOR_HOST=localhost
|
||||
PGVECTOR_PORT=5432
|
||||
PGVECTOR_DATABASE=mydb
|
||||
PGVECTOR_USER=myuser
|
||||
PGVECTOR_PASSWORD=mypassword
|
||||
|
|
@ -1,179 +0,0 @@
|
|||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
MANIFEST
|
||||
|
||||
# PyInstaller
|
||||
# Usually these files are written by a python script from a template
|
||||
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
*.py,cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
cover/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
# For a library or package, you might want to ignore these files since the code is
|
||||
# intended to run in multiple environments; otherwise, check them in:
|
||||
# .python-version
|
||||
|
||||
# pipenv
|
||||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
||||
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
|
||||
|
||||
# poetry
|
||||
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
||||
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
||||
# commonly ignored for libraries.
|
||||
#poetry.lock
|
||||
|
||||
# pdm
|
||||
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
||||
#pdm.lock
|
||||
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
||||
# in version control. See https://pdm.fming.dev/#use-with-ide
|
||||
.pdm.toml
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# pytype static type analyzer
|
||||
.pytype/
|
||||
|
||||
# Cython debug symbols
|
||||
cython_debug/
|
||||
|
||||
# PyCharm
|
||||
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
||||
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
||||
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
||||
#.idea/
|
||||
|
||||
# VS Code
|
||||
.vscode/*
|
||||
!.vscode/extensions.json
|
||||
|
||||
# Logs
|
||||
logs/
|
||||
*.log
|
||||
webIOs/output/logs/
|
||||
|
||||
# OS generated files
|
||||
Thumbs.db
|
||||
.DS_Store
|
||||
.DS_Store?
|
||||
._*
|
||||
.Spotlight-V100
|
||||
.Trashes
|
||||
ehthumbs.db
|
||||
|
||||
# FastAPI specific
|
||||
*.pyc
|
||||
uvicorn*.log
|
||||
Binary file not shown.
|
|
@ -1,147 +0,0 @@
|
|||
# A generic, single database configuration.
|
||||
|
||||
[alembic]
|
||||
# path to migration scripts.
|
||||
# this is typically a path given in POSIX (e.g. forward slashes)
|
||||
# format, relative to the token %(here)s which refers to the location of this
|
||||
# ini file
|
||||
script_location = %(here)s/alembic
|
||||
|
||||
# template used to generate migration file names; The default value is %%(rev)s_%%(slug)s
|
||||
# Uncomment the line below if you want the files to be prepended with date and time
|
||||
# see https://alembic.sqlalchemy.org/en/latest/tutorial.html#editing-the-ini-file
|
||||
# for all available tokens
|
||||
# file_template = %%(year)d_%%(month).2d_%%(day).2d_%%(hour).2d%%(minute).2d-%%(rev)s_%%(slug)s
|
||||
|
||||
# sys.path path, will be prepended to sys.path if present.
|
||||
# defaults to the current working directory. for multiple paths, the path separator
|
||||
# is defined by "path_separator" below.
|
||||
prepend_sys_path = .
|
||||
|
||||
# timezone to use when rendering the date within the migration file
|
||||
# as well as the filename.
|
||||
# If specified, requires the tzdata library which can be installed by adding
|
||||
# `alembic[tz]` to the pip requirements.
|
||||
# string value is passed to ZoneInfo()
|
||||
# leave blank for localtime
|
||||
# timezone =
|
||||
|
||||
# max length of characters to apply to the "slug" field
|
||||
# truncate_slug_length = 40
|
||||
|
||||
# set to 'true' to run the environment during
|
||||
# the 'revision' command, regardless of autogenerate
|
||||
# revision_environment = false
|
||||
|
||||
# set to 'true' to allow .pyc and .pyo files without
|
||||
# a source .py file to be detected as revisions in the
|
||||
# versions/ directory
|
||||
# sourceless = false
|
||||
|
||||
# version location specification; This defaults
|
||||
# to <script_location>/versions. When using multiple version
|
||||
# directories, initial revisions must be specified with --version-path.
|
||||
# The path separator used here should be the separator specified by "path_separator"
|
||||
# below.
|
||||
# version_locations = %(here)s/bar:%(here)s/bat:%(here)s/alembic/versions
|
||||
|
||||
# path_separator; This indicates what character is used to split lists of file
|
||||
# paths, including version_locations and prepend_sys_path within configparser
|
||||
# files such as alembic.ini.
|
||||
# The default rendered in new alembic.ini files is "os", which uses os.pathsep
|
||||
# to provide os-dependent path splitting.
|
||||
#
|
||||
# Note that in order to support legacy alembic.ini files, this default does NOT
|
||||
# take place if path_separator is not present in alembic.ini. If this
|
||||
# option is omitted entirely, fallback logic is as follows:
|
||||
#
|
||||
# 1. Parsing of the version_locations option falls back to using the legacy
|
||||
# "version_path_separator" key, which if absent then falls back to the legacy
|
||||
# behavior of splitting on spaces and/or commas.
|
||||
# 2. Parsing of the prepend_sys_path option falls back to the legacy
|
||||
# behavior of splitting on spaces, commas, or colons.
|
||||
#
|
||||
# Valid values for path_separator are:
|
||||
#
|
||||
# path_separator = :
|
||||
# path_separator = ;
|
||||
# path_separator = space
|
||||
# path_separator = newline
|
||||
#
|
||||
# Use os.pathsep. Default configuration used for new projects.
|
||||
path_separator = os
|
||||
|
||||
|
||||
# set to 'true' to search source files recursively
|
||||
# in each "version_locations" directory
|
||||
# new in Alembic version 1.10
|
||||
# recursive_version_locations = false
|
||||
|
||||
# the output encoding used when revision files
|
||||
# are written from script.py.mako
|
||||
# output_encoding = utf-8
|
||||
|
||||
# database URL. This is consumed by the user-maintained env.py script only.
|
||||
# other means of configuring database URLs may be customized within the env.py
|
||||
# file.
|
||||
# sqlalchemy.url = driver://user:pass@localhost/dbname
|
||||
|
||||
|
||||
[post_write_hooks]
|
||||
# post_write_hooks defines scripts or Python functions that are run
|
||||
# on newly generated revision scripts. See the documentation for further
|
||||
# detail and examples
|
||||
|
||||
# format using "black" - use the console_scripts runner, against the "black" entrypoint
|
||||
# hooks = black
|
||||
# black.type = console_scripts
|
||||
# black.entrypoint = black
|
||||
# black.options = -l 79 REVISION_SCRIPT_FILENAME
|
||||
|
||||
# lint with attempts to fix using "ruff" - use the module runner, against the "ruff" module
|
||||
# hooks = ruff
|
||||
# ruff.type = module
|
||||
# ruff.module = ruff
|
||||
# ruff.options = check --fix REVISION_SCRIPT_FILENAME
|
||||
|
||||
# Alternatively, use the exec runner to execute a binary found on your PATH
|
||||
# hooks = ruff
|
||||
# ruff.type = exec
|
||||
# ruff.executable = ruff
|
||||
# ruff.options = check --fix REVISION_SCRIPT_FILENAME
|
||||
|
||||
# Logging configuration. This is also consumed by the user-maintained
|
||||
# env.py script only.
|
||||
[loggers]
|
||||
keys = root,sqlalchemy,alembic
|
||||
|
||||
[handlers]
|
||||
keys = console
|
||||
|
||||
[formatters]
|
||||
keys = generic
|
||||
|
||||
[logger_root]
|
||||
level = WARNING
|
||||
handlers = console
|
||||
qualname =
|
||||
|
||||
[logger_sqlalchemy]
|
||||
level = WARNING
|
||||
handlers =
|
||||
qualname = sqlalchemy.engine
|
||||
|
||||
[logger_alembic]
|
||||
level = INFO
|
||||
handlers =
|
||||
qualname = alembic
|
||||
|
||||
[handler_console]
|
||||
class = StreamHandler
|
||||
args = (sys.stderr,)
|
||||
level = NOTSET
|
||||
formatter = generic
|
||||
|
||||
[formatter_generic]
|
||||
format = %(levelname)-5.5s [%(name)s] %(message)s
|
||||
datefmt = %H:%M:%S
|
||||
|
|
@ -1 +0,0 @@
|
|||
Generic single-database configuration with an async dbapi.
|
||||
|
|
@ -1,101 +0,0 @@
|
|||
import asyncio, os
|
||||
from logging.config import fileConfig
|
||||
|
||||
from sqlalchemy import pool
|
||||
from sqlalchemy.engine import Connection
|
||||
from sqlalchemy.ext.asyncio import async_engine_from_config
|
||||
|
||||
from alembic import context
|
||||
|
||||
# this is the Alembic Config object, which provides
|
||||
# access to the values within the .ini file in use.
|
||||
config = context.config
|
||||
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv()
|
||||
database_url = os.getenv("DATABASE_URL")
|
||||
if not database_url:
|
||||
raise ValueError("环境变量DATABASE_URL未设置")
|
||||
|
||||
config.set_main_option("sqlalchemy.url", database_url)
|
||||
|
||||
|
||||
|
||||
# Interpret the config file for Python logging.
|
||||
# This line sets up loggers basically.
|
||||
if config.config_file_name is not None:
|
||||
fileConfig(config.config_file_name)
|
||||
|
||||
# add your model's MetaData object here
|
||||
# for 'autogenerate' support
|
||||
# from myapp import mymodel
|
||||
# target_metadata = mymodel.Base.metadata
|
||||
from th_agenter.db import Base
|
||||
# from th_agenter.models import User, Conversation, Message, KnowledgeBase, Document, AgentConfig, ExcelFile, Role, UserRole, LLMConfig, Workflow, WorkflowExecution, NodeExecution, DatabaseConfig, TableMetadata
|
||||
target_metadata = Base.metadata
|
||||
|
||||
# other values from the config, defined by the needs of env.py,
|
||||
# can be acquired:
|
||||
# my_important_option = config.get_main_option("my_important_option")
|
||||
# ... etc.
|
||||
|
||||
|
||||
def run_migrations_offline() -> None:
|
||||
"""Run migrations in 'offline' mode.
|
||||
|
||||
This configures the context with just a URL
|
||||
and not an Engine, though an Engine is acceptable
|
||||
here as well. By skipping the Engine creation
|
||||
we don't even need a DBAPI to be available.
|
||||
|
||||
Calls to context.execute() here emit the given string to the
|
||||
script output.
|
||||
|
||||
"""
|
||||
url = config.get_main_option("sqlalchemy.url")
|
||||
context.configure(
|
||||
url=url,
|
||||
target_metadata=target_metadata,
|
||||
literal_binds=True,
|
||||
dialect_opts={"paramstyle": "named"},
|
||||
)
|
||||
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
def do_run_migrations(connection: Connection) -> None:
|
||||
context.configure(connection=connection, target_metadata=target_metadata)
|
||||
|
||||
with context.begin_transaction():
|
||||
context.run_migrations()
|
||||
|
||||
|
||||
async def run_async_migrations() -> None:
|
||||
"""In this scenario we need to create an Engine
|
||||
and associate a connection with the context.
|
||||
|
||||
"""
|
||||
|
||||
connectable = async_engine_from_config(
|
||||
config.get_section(config.config_ini_section, {}),
|
||||
prefix="sqlalchemy.",
|
||||
poolclass=pool.NullPool,
|
||||
)
|
||||
|
||||
async with connectable.connect() as connection:
|
||||
await connection.run_sync(do_run_migrations)
|
||||
|
||||
await connectable.dispose()
|
||||
|
||||
|
||||
def run_migrations_online() -> None:
|
||||
"""Run migrations in 'online' mode."""
|
||||
|
||||
asyncio.run(run_async_migrations())
|
||||
|
||||
|
||||
if context.is_offline_mode():
|
||||
run_migrations_offline()
|
||||
else:
|
||||
run_migrations_online()
|
||||
|
|
@ -1,28 +0,0 @@
|
|||
"""${message}
|
||||
|
||||
Revision ID: ${up_revision}
|
||||
Revises: ${down_revision | comma,n}
|
||||
Create Date: ${create_date}
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
${imports if imports else ""}
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = ${repr(up_revision)}
|
||||
down_revision: Union[str, Sequence[str], None] = ${repr(down_revision)}
|
||||
branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)}
|
||||
depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)}
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Upgrade schema."""
|
||||
${upgrades if upgrades else "pass"}
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Downgrade schema."""
|
||||
${downgrades if downgrades else "pass"}
|
||||
|
|
@ -1,359 +0,0 @@
|
|||
"""init
|
||||
|
||||
Revision ID: 1ea5548d641d
|
||||
Revises:
|
||||
Create Date: 2025-12-13 13:47:07.838600
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '1ea5548d641d'
|
||||
down_revision: Union[str, Sequence[str], None] = None
|
||||
branch_labels: Union[str, Sequence[str], None] = None
|
||||
depends_on: Union[str, Sequence[str], None] = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Upgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.create_table('agent_configs',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('enabled_tools', sa.JSON(), nullable=False),
|
||||
sa.Column('max_iterations', sa.Integer(), nullable=False),
|
||||
sa.Column('temperature', sa.String(length=10), nullable=False),
|
||||
sa.Column('system_message', sa.Text(), nullable=True),
|
||||
sa.Column('verbose', sa.Boolean(), nullable=False),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_agent_configs'))
|
||||
)
|
||||
op.create_index(op.f('ix_agent_configs_id'), 'agent_configs', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_agent_configs_name'), 'agent_configs', ['name'], unique=False)
|
||||
op.create_table('conversations',
|
||||
sa.Column('title', sa.String(length=200), nullable=False),
|
||||
sa.Column('user_id', sa.Integer(), nullable=False),
|
||||
sa.Column('knowledge_base_id', sa.Integer(), nullable=True),
|
||||
sa.Column('system_prompt', sa.Text(), nullable=True),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('temperature', sa.String(length=10), nullable=False),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('is_archived', sa.Boolean(), nullable=False),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_conversations'))
|
||||
)
|
||||
op.create_index(op.f('ix_conversations_id'), 'conversations', ['id'], unique=False)
|
||||
op.create_table('database_configs',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('db_type', sa.String(length=20), nullable=False),
|
||||
sa.Column('host', sa.String(length=255), nullable=False),
|
||||
sa.Column('port', sa.Integer(), nullable=False),
|
||||
sa.Column('database', sa.String(length=100), nullable=False),
|
||||
sa.Column('username', sa.String(length=100), nullable=False),
|
||||
sa.Column('password', sa.Text(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('connection_params', sa.JSON(), nullable=True),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_database_configs')),
|
||||
sa.UniqueConstraint('db_type', name=op.f('uq_database_configs_db_type'))
|
||||
)
|
||||
op.create_index(op.f('ix_database_configs_id'), 'database_configs', ['id'], unique=False)
|
||||
op.create_table('documents',
|
||||
sa.Column('knowledge_base_id', sa.Integer(), nullable=False),
|
||||
sa.Column('filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('original_filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('file_path', sa.String(length=500), nullable=False),
|
||||
sa.Column('file_size', sa.Integer(), nullable=False),
|
||||
sa.Column('file_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('mime_type', sa.String(length=100), nullable=True),
|
||||
sa.Column('is_processed', sa.Boolean(), nullable=False),
|
||||
sa.Column('processing_error', sa.Text(), nullable=True),
|
||||
sa.Column('content', sa.Text(), nullable=True),
|
||||
sa.Column('doc_metadata', sa.JSON(), nullable=True),
|
||||
sa.Column('chunk_count', sa.Integer(), nullable=False),
|
||||
sa.Column('embedding_model', sa.String(length=100), nullable=True),
|
||||
sa.Column('vector_ids', sa.JSON(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_documents'))
|
||||
)
|
||||
op.create_index(op.f('ix_documents_id'), 'documents', ['id'], unique=False)
|
||||
op.create_table('excel_files',
|
||||
sa.Column('original_filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('file_path', sa.String(length=500), nullable=False),
|
||||
sa.Column('file_size', sa.Integer(), nullable=False),
|
||||
sa.Column('file_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('sheet_names', sa.JSON(), nullable=False),
|
||||
sa.Column('default_sheet', sa.String(length=100), nullable=True),
|
||||
sa.Column('columns_info', sa.JSON(), nullable=False),
|
||||
sa.Column('preview_data', sa.JSON(), nullable=False),
|
||||
sa.Column('data_types', sa.JSON(), nullable=True),
|
||||
sa.Column('total_rows', sa.JSON(), nullable=True),
|
||||
sa.Column('total_columns', sa.JSON(), nullable=True),
|
||||
sa.Column('is_processed', sa.Boolean(), nullable=False),
|
||||
sa.Column('processing_error', sa.Text(), nullable=True),
|
||||
sa.Column('last_accessed', sa.DateTime(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_excel_files'))
|
||||
)
|
||||
op.create_index(op.f('ix_excel_files_id'), 'excel_files', ['id'], unique=False)
|
||||
op.create_table('knowledge_bases',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('embedding_model', sa.String(length=100), nullable=False),
|
||||
sa.Column('chunk_size', sa.Integer(), nullable=False),
|
||||
sa.Column('chunk_overlap', sa.Integer(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('vector_db_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('collection_name', sa.String(length=100), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_knowledge_bases'))
|
||||
)
|
||||
op.create_index(op.f('ix_knowledge_bases_id'), 'knowledge_bases', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_knowledge_bases_name'), 'knowledge_bases', ['name'], unique=False)
|
||||
op.create_table('llm_configs',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('provider', sa.String(length=50), nullable=False),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('api_key', sa.String(length=500), nullable=False),
|
||||
sa.Column('base_url', sa.String(length=200), nullable=True),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('temperature', sa.Float(), nullable=False),
|
||||
sa.Column('top_p', sa.Float(), nullable=False),
|
||||
sa.Column('frequency_penalty', sa.Float(), nullable=False),
|
||||
sa.Column('presence_penalty', sa.Float(), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_embedding', sa.Boolean(), nullable=False),
|
||||
sa.Column('extra_config', sa.JSON(), nullable=True),
|
||||
sa.Column('usage_count', sa.Integer(), nullable=False),
|
||||
sa.Column('last_used_at', sa.DateTime(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_llm_configs'))
|
||||
)
|
||||
op.create_index(op.f('ix_llm_configs_id'), 'llm_configs', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_llm_configs_name'), 'llm_configs', ['name'], unique=False)
|
||||
op.create_index(op.f('ix_llm_configs_provider'), 'llm_configs', ['provider'], unique=False)
|
||||
op.create_table('messages',
|
||||
sa.Column('conversation_id', sa.Integer(), nullable=False),
|
||||
sa.Column('role', sa.Enum('USER', 'ASSISTANT', 'SYSTEM', name='messagerole'), nullable=False),
|
||||
sa.Column('content', sa.Text(), nullable=False),
|
||||
sa.Column('message_type', sa.Enum('TEXT', 'IMAGE', 'FILE', 'AUDIO', name='messagetype'), nullable=False),
|
||||
sa.Column('message_metadata', sa.JSON(), nullable=True),
|
||||
sa.Column('context_documents', sa.JSON(), nullable=True),
|
||||
sa.Column('prompt_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('completion_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('total_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_messages'))
|
||||
)
|
||||
op.create_index(op.f('ix_messages_id'), 'messages', ['id'], unique=False)
|
||||
op.create_table('roles',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('code', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('is_system', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_roles'))
|
||||
)
|
||||
op.create_index(op.f('ix_roles_code'), 'roles', ['code'], unique=True)
|
||||
op.create_index(op.f('ix_roles_id'), 'roles', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_roles_name'), 'roles', ['name'], unique=True)
|
||||
op.create_table('table_metadata',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('table_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('table_schema', sa.String(length=50), nullable=False),
|
||||
sa.Column('table_type', sa.String(length=20), nullable=False),
|
||||
sa.Column('table_comment', sa.Text(), nullable=True),
|
||||
sa.Column('database_config_id', sa.Integer(), nullable=True),
|
||||
sa.Column('columns_info', sa.JSON(), nullable=False),
|
||||
sa.Column('primary_keys', sa.JSON(), nullable=True),
|
||||
sa.Column('foreign_keys', sa.JSON(), nullable=True),
|
||||
sa.Column('indexes', sa.JSON(), nullable=True),
|
||||
sa.Column('sample_data', sa.JSON(), nullable=True),
|
||||
sa.Column('row_count', sa.Integer(), nullable=False),
|
||||
sa.Column('is_enabled_for_qa', sa.Boolean(), nullable=False),
|
||||
sa.Column('qa_description', sa.Text(), nullable=True),
|
||||
sa.Column('business_context', sa.Text(), nullable=True),
|
||||
sa.Column('last_synced_at', sa.DateTime(timezone=True), nullable=True),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_table_metadata'))
|
||||
)
|
||||
op.create_index(op.f('ix_table_metadata_id'), 'table_metadata', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_table_metadata_table_name'), 'table_metadata', ['table_name'], unique=False)
|
||||
op.create_table('users',
|
||||
sa.Column('username', sa.String(length=50), nullable=False),
|
||||
sa.Column('email', sa.String(length=100), nullable=False),
|
||||
sa.Column('hashed_password', sa.String(length=255), nullable=False),
|
||||
sa.Column('full_name', sa.String(length=100), nullable=True),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('avatar_url', sa.String(length=255), nullable=True),
|
||||
sa.Column('bio', sa.Text(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_users'))
|
||||
)
|
||||
op.create_index(op.f('ix_users_email'), 'users', ['email'], unique=True)
|
||||
op.create_index(op.f('ix_users_id'), 'users', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_users_username'), 'users', ['username'], unique=True)
|
||||
op.create_table('user_roles',
|
||||
sa.Column('user_id', sa.Integer(), nullable=False),
|
||||
sa.Column('role_id', sa.Integer(), nullable=False),
|
||||
sa.ForeignKeyConstraint(['role_id'], ['roles.id'], name=op.f('fk_user_roles_role_id_roles')),
|
||||
sa.ForeignKeyConstraint(['user_id'], ['users.id'], name=op.f('fk_user_roles_user_id_users')),
|
||||
sa.PrimaryKeyConstraint('user_id', 'role_id', name=op.f('pk_user_roles'))
|
||||
)
|
||||
op.create_table('workflows',
|
||||
sa.Column('name', sa.String(length=100), nullable=False, comment='工作流名称'),
|
||||
sa.Column('description', sa.Text(), nullable=True, comment='工作流描述'),
|
||||
sa.Column('status', sa.Enum('DRAFT', 'PUBLISHED', 'ARCHIVED', name='workflowstatus'), nullable=False, comment='工作流状态'),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False, comment='是否激活'),
|
||||
sa.Column('definition', sa.JSON(), nullable=False, comment='工作流定义'),
|
||||
sa.Column('version', sa.String(length=20), nullable=False, comment='版本号'),
|
||||
sa.Column('owner_id', sa.Integer(), nullable=False, comment='所有者ID'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['owner_id'], ['users.id'], name=op.f('fk_workflows_owner_id_users')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_workflows'))
|
||||
)
|
||||
op.create_index(op.f('ix_workflows_id'), 'workflows', ['id'], unique=False)
|
||||
op.create_table('workflow_executions',
|
||||
sa.Column('workflow_id', sa.Integer(), nullable=False, comment='工作流ID'),
|
||||
sa.Column('status', sa.Enum('PENDING', 'RUNNING', 'COMPLETED', 'FAILED', 'CANCELLED', name='executionstatus'), nullable=False, comment='执行状态'),
|
||||
sa.Column('input_data', sa.JSON(), nullable=True, comment='输入数据'),
|
||||
sa.Column('output_data', sa.JSON(), nullable=True, comment='输出数据'),
|
||||
sa.Column('started_at', sa.String(length=50), nullable=True, comment='开始时间'),
|
||||
sa.Column('completed_at', sa.String(length=50), nullable=True, comment='完成时间'),
|
||||
sa.Column('error_message', sa.Text(), nullable=True, comment='错误信息'),
|
||||
sa.Column('executor_id', sa.Integer(), nullable=False, comment='执行者ID'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['executor_id'], ['users.id'], name=op.f('fk_workflow_executions_executor_id_users')),
|
||||
sa.ForeignKeyConstraint(['workflow_id'], ['workflows.id'], name=op.f('fk_workflow_executions_workflow_id_workflows')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_workflow_executions'))
|
||||
)
|
||||
op.create_index(op.f('ix_workflow_executions_id'), 'workflow_executions', ['id'], unique=False)
|
||||
op.create_table('node_executions',
|
||||
sa.Column('workflow_execution_id', sa.Integer(), nullable=False, comment='工作流执行ID'),
|
||||
sa.Column('node_id', sa.String(length=50), nullable=False, comment='节点ID'),
|
||||
sa.Column('node_type', sa.Enum('START', 'END', 'LLM', 'CONDITION', 'LOOP', 'CODE', 'HTTP', 'TOOL', name='nodetype'), nullable=False, comment='节点类型'),
|
||||
sa.Column('node_name', sa.String(length=100), nullable=False, comment='节点名称'),
|
||||
sa.Column('status', sa.Enum('PENDING', 'RUNNING', 'COMPLETED', 'FAILED', 'CANCELLED', name='executionstatus'), nullable=False, comment='执行状态'),
|
||||
sa.Column('input_data', sa.JSON(), nullable=True, comment='输入数据'),
|
||||
sa.Column('output_data', sa.JSON(), nullable=True, comment='输出数据'),
|
||||
sa.Column('started_at', sa.String(length=50), nullable=True, comment='开始时间'),
|
||||
sa.Column('completed_at', sa.String(length=50), nullable=True, comment='完成时间'),
|
||||
sa.Column('duration_ms', sa.Integer(), nullable=True, comment='执行时长(毫秒)'),
|
||||
sa.Column('error_message', sa.Text(), nullable=True, comment='错误信息'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['workflow_execution_id'], ['workflow_executions.id'], name=op.f('fk_node_executions_workflow_execution_id_workflow_executions')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_node_executions'))
|
||||
)
|
||||
op.create_index(op.f('ix_node_executions_id'), 'node_executions', ['id'], unique=False)
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Downgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.drop_index(op.f('ix_node_executions_id'), table_name='node_executions')
|
||||
op.drop_table('node_executions')
|
||||
op.drop_index(op.f('ix_workflow_executions_id'), table_name='workflow_executions')
|
||||
op.drop_table('workflow_executions')
|
||||
op.drop_index(op.f('ix_workflows_id'), table_name='workflows')
|
||||
op.drop_table('workflows')
|
||||
op.drop_table('user_roles')
|
||||
op.drop_index(op.f('ix_users_username'), table_name='users')
|
||||
op.drop_index(op.f('ix_users_id'), table_name='users')
|
||||
op.drop_index(op.f('ix_users_email'), table_name='users')
|
||||
op.drop_table('users')
|
||||
op.drop_index(op.f('ix_table_metadata_table_name'), table_name='table_metadata')
|
||||
op.drop_index(op.f('ix_table_metadata_id'), table_name='table_metadata')
|
||||
op.drop_table('table_metadata')
|
||||
op.drop_index(op.f('ix_roles_name'), table_name='roles')
|
||||
op.drop_index(op.f('ix_roles_id'), table_name='roles')
|
||||
op.drop_index(op.f('ix_roles_code'), table_name='roles')
|
||||
op.drop_table('roles')
|
||||
op.drop_index(op.f('ix_messages_id'), table_name='messages')
|
||||
op.drop_table('messages')
|
||||
op.drop_index(op.f('ix_llm_configs_provider'), table_name='llm_configs')
|
||||
op.drop_index(op.f('ix_llm_configs_name'), table_name='llm_configs')
|
||||
op.drop_index(op.f('ix_llm_configs_id'), table_name='llm_configs')
|
||||
op.drop_table('llm_configs')
|
||||
op.drop_index(op.f('ix_knowledge_bases_name'), table_name='knowledge_bases')
|
||||
op.drop_index(op.f('ix_knowledge_bases_id'), table_name='knowledge_bases')
|
||||
op.drop_table('knowledge_bases')
|
||||
op.drop_index(op.f('ix_excel_files_id'), table_name='excel_files')
|
||||
op.drop_table('excel_files')
|
||||
op.drop_index(op.f('ix_documents_id'), table_name='documents')
|
||||
op.drop_table('documents')
|
||||
op.drop_index(op.f('ix_database_configs_id'), table_name='database_configs')
|
||||
op.drop_table('database_configs')
|
||||
op.drop_index(op.f('ix_conversations_id'), table_name='conversations')
|
||||
op.drop_table('conversations')
|
||||
op.drop_index(op.f('ix_agent_configs_name'), table_name='agent_configs')
|
||||
op.drop_index(op.f('ix_agent_configs_id'), table_name='agent_configs')
|
||||
op.drop_table('agent_configs')
|
||||
# ### end Alembic commands ###
|
||||
|
|
@ -1,359 +0,0 @@
|
|||
"""Initial migration
|
||||
|
||||
Revision ID: 424646027786
|
||||
Revises:
|
||||
Create Date: 2025-12-16 09:56:45.172954
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '424646027786'
|
||||
down_revision: Union[str, Sequence[str], None] = None
|
||||
branch_labels: Union[str, Sequence[str], None] = None
|
||||
depends_on: Union[str, Sequence[str], None] = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Upgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.create_table('agent_configs',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('enabled_tools', sa.JSON(), nullable=False),
|
||||
sa.Column('max_iterations', sa.Integer(), nullable=False),
|
||||
sa.Column('temperature', sa.String(length=10), nullable=False),
|
||||
sa.Column('system_message', sa.Text(), nullable=True),
|
||||
sa.Column('verbose', sa.Boolean(), nullable=False),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_agent_configs'))
|
||||
)
|
||||
op.create_index(op.f('ix_agent_configs_id'), 'agent_configs', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_agent_configs_name'), 'agent_configs', ['name'], unique=False)
|
||||
op.create_table('conversations',
|
||||
sa.Column('title', sa.String(length=200), nullable=False),
|
||||
sa.Column('user_id', sa.Integer(), nullable=False),
|
||||
sa.Column('knowledge_base_id', sa.Integer(), nullable=True),
|
||||
sa.Column('system_prompt', sa.Text(), nullable=True),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('temperature', sa.String(length=10), nullable=False),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('is_archived', sa.Boolean(), nullable=False),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_conversations'))
|
||||
)
|
||||
op.create_index(op.f('ix_conversations_id'), 'conversations', ['id'], unique=False)
|
||||
op.create_table('database_configs',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('db_type', sa.String(length=20), nullable=False),
|
||||
sa.Column('host', sa.String(length=255), nullable=False),
|
||||
sa.Column('port', sa.Integer(), nullable=False),
|
||||
sa.Column('database', sa.String(length=100), nullable=False),
|
||||
sa.Column('username', sa.String(length=100), nullable=False),
|
||||
sa.Column('password', sa.Text(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('connection_params', sa.JSON(), nullable=True),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_database_configs')),
|
||||
sa.UniqueConstraint('db_type', name=op.f('uq_database_configs_db_type'))
|
||||
)
|
||||
op.create_index(op.f('ix_database_configs_id'), 'database_configs', ['id'], unique=False)
|
||||
op.create_table('documents',
|
||||
sa.Column('knowledge_base_id', sa.Integer(), nullable=False),
|
||||
sa.Column('filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('original_filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('file_path', sa.String(length=500), nullable=False),
|
||||
sa.Column('file_size', sa.Integer(), nullable=False),
|
||||
sa.Column('file_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('mime_type', sa.String(length=100), nullable=True),
|
||||
sa.Column('is_processed', sa.Boolean(), nullable=False),
|
||||
sa.Column('processing_error', sa.Text(), nullable=True),
|
||||
sa.Column('content', sa.Text(), nullable=True),
|
||||
sa.Column('doc_metadata', sa.JSON(), nullable=True),
|
||||
sa.Column('chunk_count', sa.Integer(), nullable=False),
|
||||
sa.Column('embedding_model', sa.String(length=100), nullable=True),
|
||||
sa.Column('vector_ids', sa.JSON(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_documents'))
|
||||
)
|
||||
op.create_index(op.f('ix_documents_id'), 'documents', ['id'], unique=False)
|
||||
op.create_table('excel_files',
|
||||
sa.Column('original_filename', sa.String(length=255), nullable=False),
|
||||
sa.Column('file_path', sa.String(length=500), nullable=False),
|
||||
sa.Column('file_size', sa.Integer(), nullable=False),
|
||||
sa.Column('file_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('sheet_names', sa.JSON(), nullable=False),
|
||||
sa.Column('default_sheet', sa.String(length=100), nullable=True),
|
||||
sa.Column('columns_info', sa.JSON(), nullable=False),
|
||||
sa.Column('preview_data', sa.JSON(), nullable=False),
|
||||
sa.Column('data_types', sa.JSON(), nullable=True),
|
||||
sa.Column('total_rows', sa.JSON(), nullable=True),
|
||||
sa.Column('total_columns', sa.JSON(), nullable=True),
|
||||
sa.Column('is_processed', sa.Boolean(), nullable=False),
|
||||
sa.Column('processing_error', sa.Text(), nullable=True),
|
||||
sa.Column('last_accessed', sa.DateTime(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_excel_files'))
|
||||
)
|
||||
op.create_index(op.f('ix_excel_files_id'), 'excel_files', ['id'], unique=False)
|
||||
op.create_table('knowledge_bases',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('embedding_model', sa.String(length=100), nullable=False),
|
||||
sa.Column('chunk_size', sa.Integer(), nullable=False),
|
||||
sa.Column('chunk_overlap', sa.Integer(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('vector_db_type', sa.String(length=50), nullable=False),
|
||||
sa.Column('collection_name', sa.String(length=100), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_knowledge_bases'))
|
||||
)
|
||||
op.create_index(op.f('ix_knowledge_bases_id'), 'knowledge_bases', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_knowledge_bases_name'), 'knowledge_bases', ['name'], unique=False)
|
||||
op.create_table('llm_configs',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('provider', sa.String(length=50), nullable=False),
|
||||
sa.Column('model_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('api_key', sa.String(length=500), nullable=False),
|
||||
sa.Column('base_url', sa.String(length=200), nullable=True),
|
||||
sa.Column('max_tokens', sa.Integer(), nullable=False),
|
||||
sa.Column('temperature', sa.Float(), nullable=False),
|
||||
sa.Column('top_p', sa.Float(), nullable=False),
|
||||
sa.Column('frequency_penalty', sa.Float(), nullable=False),
|
||||
sa.Column('presence_penalty', sa.Float(), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_default', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_embedding', sa.Boolean(), nullable=False),
|
||||
sa.Column('extra_config', sa.JSON(), nullable=True),
|
||||
sa.Column('usage_count', sa.Integer(), nullable=False),
|
||||
sa.Column('last_used_at', sa.DateTime(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_llm_configs'))
|
||||
)
|
||||
op.create_index(op.f('ix_llm_configs_id'), 'llm_configs', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_llm_configs_name'), 'llm_configs', ['name'], unique=False)
|
||||
op.create_index(op.f('ix_llm_configs_provider'), 'llm_configs', ['provider'], unique=False)
|
||||
op.create_table('messages',
|
||||
sa.Column('conversation_id', sa.Integer(), nullable=False),
|
||||
sa.Column('role', sa.Enum('USER', 'ASSISTANT', 'SYSTEM', name='messagerole'), nullable=False),
|
||||
sa.Column('content', sa.Text(), nullable=False),
|
||||
sa.Column('message_type', sa.Enum('TEXT', 'IMAGE', 'FILE', 'AUDIO', name='messagetype'), nullable=False),
|
||||
sa.Column('message_metadata', sa.JSON(), nullable=True),
|
||||
sa.Column('context_documents', sa.JSON(), nullable=True),
|
||||
sa.Column('prompt_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('completion_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('total_tokens', sa.Integer(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_messages'))
|
||||
)
|
||||
op.create_index(op.f('ix_messages_id'), 'messages', ['id'], unique=False)
|
||||
op.create_table('roles',
|
||||
sa.Column('name', sa.String(length=100), nullable=False),
|
||||
sa.Column('code', sa.String(length=100), nullable=False),
|
||||
sa.Column('description', sa.Text(), nullable=True),
|
||||
sa.Column('is_system', sa.Boolean(), nullable=False),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_roles'))
|
||||
)
|
||||
op.create_index(op.f('ix_roles_code'), 'roles', ['code'], unique=True)
|
||||
op.create_index(op.f('ix_roles_id'), 'roles', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_roles_name'), 'roles', ['name'], unique=True)
|
||||
op.create_table('table_metadata',
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('table_name', sa.String(length=100), nullable=False),
|
||||
sa.Column('table_schema', sa.String(length=50), nullable=False),
|
||||
sa.Column('table_type', sa.String(length=20), nullable=False),
|
||||
sa.Column('table_comment', sa.Text(), nullable=True),
|
||||
sa.Column('database_config_id', sa.Integer(), nullable=True),
|
||||
sa.Column('columns_info', sa.JSON(), nullable=False),
|
||||
sa.Column('primary_keys', sa.JSON(), nullable=True),
|
||||
sa.Column('foreign_keys', sa.JSON(), nullable=True),
|
||||
sa.Column('indexes', sa.JSON(), nullable=True),
|
||||
sa.Column('sample_data', sa.JSON(), nullable=True),
|
||||
sa.Column('row_count', sa.Integer(), nullable=False),
|
||||
sa.Column('is_enabled_for_qa', sa.Boolean(), nullable=False),
|
||||
sa.Column('qa_description', sa.Text(), nullable=True),
|
||||
sa.Column('business_context', sa.Text(), nullable=True),
|
||||
sa.Column('last_synced_at', sa.DateTime(timezone=True), nullable=True),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_table_metadata'))
|
||||
)
|
||||
op.create_index(op.f('ix_table_metadata_id'), 'table_metadata', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_table_metadata_table_name'), 'table_metadata', ['table_name'], unique=False)
|
||||
op.create_table('users',
|
||||
sa.Column('username', sa.String(length=50), nullable=False),
|
||||
sa.Column('email', sa.String(length=100), nullable=False),
|
||||
sa.Column('hashed_password', sa.String(length=255), nullable=False),
|
||||
sa.Column('full_name', sa.String(length=100), nullable=True),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False),
|
||||
sa.Column('avatar_url', sa.String(length=255), nullable=True),
|
||||
sa.Column('bio', sa.Text(), nullable=True),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_users'))
|
||||
)
|
||||
op.create_index(op.f('ix_users_email'), 'users', ['email'], unique=True)
|
||||
op.create_index(op.f('ix_users_id'), 'users', ['id'], unique=False)
|
||||
op.create_index(op.f('ix_users_username'), 'users', ['username'], unique=True)
|
||||
op.create_table('user_roles',
|
||||
sa.Column('user_id', sa.Integer(), nullable=False),
|
||||
sa.Column('role_id', sa.Integer(), nullable=False),
|
||||
sa.ForeignKeyConstraint(['role_id'], ['roles.id'], name=op.f('fk_user_roles_role_id_roles')),
|
||||
sa.ForeignKeyConstraint(['user_id'], ['users.id'], name=op.f('fk_user_roles_user_id_users')),
|
||||
sa.PrimaryKeyConstraint('user_id', 'role_id', name=op.f('pk_user_roles'))
|
||||
)
|
||||
op.create_table('workflows',
|
||||
sa.Column('name', sa.String(length=100), nullable=False, comment='工作流名称'),
|
||||
sa.Column('description', sa.Text(), nullable=True, comment='工作流描述'),
|
||||
sa.Column('status', sa.Enum('DRAFT', 'PUBLISHED', 'ARCHIVED', name='workflowstatus'), nullable=False, comment='工作流状态'),
|
||||
sa.Column('is_active', sa.Boolean(), nullable=False, comment='是否激活'),
|
||||
sa.Column('definition', sa.JSON(), nullable=False, comment='工作流定义'),
|
||||
sa.Column('version', sa.String(length=20), nullable=False, comment='版本号'),
|
||||
sa.Column('owner_id', sa.Integer(), nullable=False, comment='所有者ID'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['owner_id'], ['users.id'], name=op.f('fk_workflows_owner_id_users')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_workflows'))
|
||||
)
|
||||
op.create_index(op.f('ix_workflows_id'), 'workflows', ['id'], unique=False)
|
||||
op.create_table('workflow_executions',
|
||||
sa.Column('workflow_id', sa.Integer(), nullable=False, comment='工作流ID'),
|
||||
sa.Column('status', sa.Enum('PENDING', 'RUNNING', 'COMPLETED', 'FAILED', 'CANCELLED', name='executionstatus'), nullable=False, comment='执行状态'),
|
||||
sa.Column('input_data', sa.JSON(), nullable=True, comment='输入数据'),
|
||||
sa.Column('output_data', sa.JSON(), nullable=True, comment='输出数据'),
|
||||
sa.Column('started_at', sa.String(length=50), nullable=True, comment='开始时间'),
|
||||
sa.Column('completed_at', sa.String(length=50), nullable=True, comment='完成时间'),
|
||||
sa.Column('error_message', sa.Text(), nullable=True, comment='错误信息'),
|
||||
sa.Column('executor_id', sa.Integer(), nullable=False, comment='执行者ID'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['executor_id'], ['users.id'], name=op.f('fk_workflow_executions_executor_id_users')),
|
||||
sa.ForeignKeyConstraint(['workflow_id'], ['workflows.id'], name=op.f('fk_workflow_executions_workflow_id_workflows')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_workflow_executions'))
|
||||
)
|
||||
op.create_index(op.f('ix_workflow_executions_id'), 'workflow_executions', ['id'], unique=False)
|
||||
op.create_table('node_executions',
|
||||
sa.Column('workflow_execution_id', sa.Integer(), nullable=False, comment='工作流执行ID'),
|
||||
sa.Column('node_id', sa.String(length=50), nullable=False, comment='节点ID'),
|
||||
sa.Column('node_type', sa.Enum('START', 'END', 'LLM', 'CONDITION', 'LOOP', 'CODE', 'HTTP', 'TOOL', name='nodetype'), nullable=False, comment='节点类型'),
|
||||
sa.Column('node_name', sa.String(length=100), nullable=False, comment='节点名称'),
|
||||
sa.Column('status', sa.Enum('PENDING', 'RUNNING', 'COMPLETED', 'FAILED', 'CANCELLED', name='executionstatus'), nullable=False, comment='执行状态'),
|
||||
sa.Column('input_data', sa.JSON(), nullable=True, comment='输入数据'),
|
||||
sa.Column('output_data', sa.JSON(), nullable=True, comment='输出数据'),
|
||||
sa.Column('started_at', sa.String(length=50), nullable=True, comment='开始时间'),
|
||||
sa.Column('completed_at', sa.String(length=50), nullable=True, comment='完成时间'),
|
||||
sa.Column('duration_ms', sa.Integer(), nullable=True, comment='执行时长(毫秒)'),
|
||||
sa.Column('error_message', sa.Text(), nullable=True, comment='错误信息'),
|
||||
sa.Column('id', sa.Integer(), nullable=False),
|
||||
sa.Column('created_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('updated_at', sa.DateTime(), nullable=False),
|
||||
sa.Column('created_by', sa.Integer(), nullable=True),
|
||||
sa.Column('updated_by', sa.Integer(), nullable=True),
|
||||
sa.ForeignKeyConstraint(['workflow_execution_id'], ['workflow_executions.id'], name=op.f('fk_node_executions_workflow_execution_id_workflow_executions')),
|
||||
sa.PrimaryKeyConstraint('id', name=op.f('pk_node_executions'))
|
||||
)
|
||||
op.create_index(op.f('ix_node_executions_id'), 'node_executions', ['id'], unique=False)
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Downgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.drop_index(op.f('ix_node_executions_id'), table_name='node_executions')
|
||||
op.drop_table('node_executions')
|
||||
op.drop_index(op.f('ix_workflow_executions_id'), table_name='workflow_executions')
|
||||
op.drop_table('workflow_executions')
|
||||
op.drop_index(op.f('ix_workflows_id'), table_name='workflows')
|
||||
op.drop_table('workflows')
|
||||
op.drop_table('user_roles')
|
||||
op.drop_index(op.f('ix_users_username'), table_name='users')
|
||||
op.drop_index(op.f('ix_users_id'), table_name='users')
|
||||
op.drop_index(op.f('ix_users_email'), table_name='users')
|
||||
op.drop_table('users')
|
||||
op.drop_index(op.f('ix_table_metadata_table_name'), table_name='table_metadata')
|
||||
op.drop_index(op.f('ix_table_metadata_id'), table_name='table_metadata')
|
||||
op.drop_table('table_metadata')
|
||||
op.drop_index(op.f('ix_roles_name'), table_name='roles')
|
||||
op.drop_index(op.f('ix_roles_id'), table_name='roles')
|
||||
op.drop_index(op.f('ix_roles_code'), table_name='roles')
|
||||
op.drop_table('roles')
|
||||
op.drop_index(op.f('ix_messages_id'), table_name='messages')
|
||||
op.drop_table('messages')
|
||||
op.drop_index(op.f('ix_llm_configs_provider'), table_name='llm_configs')
|
||||
op.drop_index(op.f('ix_llm_configs_name'), table_name='llm_configs')
|
||||
op.drop_index(op.f('ix_llm_configs_id'), table_name='llm_configs')
|
||||
op.drop_table('llm_configs')
|
||||
op.drop_index(op.f('ix_knowledge_bases_name'), table_name='knowledge_bases')
|
||||
op.drop_index(op.f('ix_knowledge_bases_id'), table_name='knowledge_bases')
|
||||
op.drop_table('knowledge_bases')
|
||||
op.drop_index(op.f('ix_excel_files_id'), table_name='excel_files')
|
||||
op.drop_table('excel_files')
|
||||
op.drop_index(op.f('ix_documents_id'), table_name='documents')
|
||||
op.drop_table('documents')
|
||||
op.drop_index(op.f('ix_database_configs_id'), table_name='database_configs')
|
||||
op.drop_table('database_configs')
|
||||
op.drop_index(op.f('ix_conversations_id'), table_name='conversations')
|
||||
op.drop_table('conversations')
|
||||
op.drop_index(op.f('ix_agent_configs_name'), table_name='agent_configs')
|
||||
op.drop_index(op.f('ix_agent_configs_id'), table_name='agent_configs')
|
||||
op.drop_table('agent_configs')
|
||||
# ### end Alembic commands ###
|
||||
|
|
@ -1,34 +0,0 @@
|
|||
"""Add message_count and last_message_at to conversations
|
||||
|
||||
Revision ID: 8da391c6e2b7
|
||||
Revises: 424646027786
|
||||
Create Date: 2025-12-19 16:16:29.943314
|
||||
|
||||
"""
|
||||
from typing import Sequence, Union
|
||||
|
||||
from alembic import op
|
||||
import sqlalchemy as sa
|
||||
|
||||
|
||||
# revision identifiers, used by Alembic.
|
||||
revision: str = '8da391c6e2b7'
|
||||
down_revision: Union[str, Sequence[str], None] = '424646027786'
|
||||
branch_labels: Union[str, Sequence[str], None] = None
|
||||
depends_on: Union[str, Sequence[str], None] = None
|
||||
|
||||
|
||||
def upgrade() -> None:
|
||||
"""Upgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.add_column('conversations', sa.Column('message_count', sa.Integer(), nullable=False))
|
||||
op.add_column('conversations', sa.Column('last_message_at', sa.DateTime(), nullable=True))
|
||||
# ### end Alembic commands ###
|
||||
|
||||
|
||||
def downgrade() -> None:
|
||||
"""Downgrade schema."""
|
||||
# ### commands auto generated by Alembic - please adjust! ###
|
||||
op.drop_column('conversations', 'last_message_at')
|
||||
op.drop_column('conversations', 'message_count')
|
||||
# ### end Alembic commands ###
|
||||
|
|
@ -1,66 +0,0 @@
|
|||
import re
|
||||
import traceback
|
||||
from loguru import logger
|
||||
|
||||
class DrGraphSession:
|
||||
def __init__(self, stepIndex: int, msg: str, session_id: str):
|
||||
logger.info(f"DrGraphSession.__init__: stepIndex={stepIndex}, msg={msg}, session_id={session_id}")
|
||||
self.stepIndex = stepIndex
|
||||
self.session_id = session_id
|
||||
|
||||
match = re.search(r";(-\d+)", msg);
|
||||
level = -3
|
||||
if match:
|
||||
level = int(match.group(1))
|
||||
value = value.replace(f";{level}", "")
|
||||
level = -3 + level
|
||||
|
||||
if "警告" in value or value.startswith("WARNING"):
|
||||
self.log_warning(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
elif "异常" in value or value.startswith("EXCEPTION"):
|
||||
self.log_exception(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
elif "成功" in value or value.startswith("SUCCESS"):
|
||||
self.log_success(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
elif "开始" in value or value.startswith("START"):
|
||||
self.log_success(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
elif "失败" in value or value.startswith("ERROR"):
|
||||
self.log_error(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
else:
|
||||
self.log_info(f"第 {self.stepIndex} 步 - {value}", level = level)
|
||||
|
||||
def log_prefix(self) -> str:
|
||||
"""Get log prefix with session ID and desc."""
|
||||
return f"〖Session{self.session_id}〗"
|
||||
|
||||
def parse_source_pos(self, level: int):
|
||||
pos = (traceback.format_stack())[level - 1].strip().split('\n')[0]
|
||||
match = re.search(r"File \"(.+?)\", line (\d+), in (\w+)", pos);
|
||||
if match:
|
||||
file = match.group(1).replace("F:\\DrGraph_Python\\FastAPI\\", "")
|
||||
pos = f"{file}:{match.group(2)} in {match.group(3)}"
|
||||
return pos
|
||||
|
||||
def log_info(self, msg: str, level: int = -2):
|
||||
"""Log info message with session ID."""
|
||||
pos = self.parse_source_pos(level)
|
||||
logger.info(f"{self.log_prefix()} {msg} >>> @ {pos}")
|
||||
|
||||
def log_success(self, msg: str, level: int = -2):
|
||||
"""Log success message with session ID."""
|
||||
pos = self.parse_source_pos(level)
|
||||
logger.success(f"{self.log_prefix()} {msg} >>> @ {pos}")
|
||||
|
||||
def log_warning(self, msg: str, level: int = -2):
|
||||
"""Log warning message with session ID."""
|
||||
pos = self.parse_source_pos(level)
|
||||
logger.warning(f"{self.log_prefix()} {msg} >>> @ {pos}")
|
||||
|
||||
def log_error(self, msg: str, level: int = -2):
|
||||
"""Log error message with session ID."""
|
||||
pos = self.parse_source_pos(level)
|
||||
logger.error(f"{self.log_prefix()} {msg} >>> @ {pos}")
|
||||
|
||||
def log_exception(self, msg: str, level: int = -2):
|
||||
"""Log exception message with session ID."""
|
||||
pos = self.parse_source_pos(level)
|
||||
logger.exception(f"{self.log_prefix()} {msg} >>> @ {pos}")
|
||||
|
|
@ -1,42 +0,0 @@
|
|||
from sqlalchemy import create_engine, inspect
|
||||
from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
|
||||
from sqlalchemy.orm import sessionmaker
|
||||
import asyncio
|
||||
import os
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# 加载环境变量
|
||||
load_dotenv()
|
||||
|
||||
async def check_table_constraints():
|
||||
try:
|
||||
# 获取数据库连接字符串
|
||||
DATABASE_URL = os.getenv("DATABASE_URL", "mysql+asyncmy://root:123456@localhost:3306/th_agenter")
|
||||
|
||||
# 创建异步引擎
|
||||
engine = create_async_engine(DATABASE_URL, echo=True)
|
||||
|
||||
# 创建会话
|
||||
async_session = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
|
||||
|
||||
async with async_session() as session:
|
||||
# 获取数据库连接
|
||||
async with session.begin():
|
||||
# 使用inspect查看表结构
|
||||
inspector = inspect(engine)
|
||||
|
||||
# 获取messages表的所有约束
|
||||
constraints = await engine.run_sync(inspector.get_table_constraints, 'messages')
|
||||
print("Messages表的所有约束:")
|
||||
for constraint in constraints:
|
||||
print(f" 约束名称: {constraint['name']}, 类型: {constraint['type']}")
|
||||
if constraint['type'] == 'PRIMARY KEY':
|
||||
print(f" 主键约束列: {constraint['constrained_columns']}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"检查约束时出错: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(check_table_constraints())
|
||||
|
|
@ -1,9 +0,0 @@
|
|||
import jwt
|
||||
import inspect
|
||||
|
||||
print(f"jwt module path: {inspect.getfile(jwt)}")
|
||||
print(f"jwt module attributes: {dir(jwt)}")
|
||||
try:
|
||||
print(f"jwt module __version__: {jwt.__version__}")
|
||||
except AttributeError:
|
||||
print("jwt module has no __version__ attribute")
|
||||
|
|
@ -11,7 +11,7 @@ app:
|
|||
file:
|
||||
upload_dir: "./data/uploads"
|
||||
max_size: 10485760 # 10MB
|
||||
allowed_extensions: [".txt", ".pdf", ".docx", ".md"]
|
||||
allowed_extensions: [".txt", ".pdf", ".docx", ".doc", ".md"]
|
||||
chunk_size: 1000
|
||||
chunk_overlap: 200
|
||||
semantic_splitter_enabled: true # 启用语义分割器
|
||||
|
|
@ -46,4 +46,11 @@ cors:
|
|||
chat:
|
||||
max_history_length: 10
|
||||
system_prompt: "你是一个有用的AI助手，请根据提供的上下文信息回答用户的问题。"
|
||||
max_response_tokens: 1000
|
||||
max_response_tokens: 1000
|
||||
|
||||
# Redis Configuration
|
||||
redis:
|
||||
host: "localhost"
|
||||
port: 6379
|
||||
db: 0
|
||||
password: null
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,40 @@
|
|||
|
||||
|
||||
|
||||
2025.10.13-2025.10.17
|
||||
|
||||
1、项目支撑
|
||||
|
||||
1.1）边缘计算项目评估支撑 -- 提供算法，确定提供算法模型，100%；
|
||||
1.2）陕西交控算法训练 ，待提供素材；
|
||||
1.3）水利标书文件算法部分补充，100%；
|
||||
1.4）溧宁高速算法优化，已确定问题，待排期处理。
|
||||
1.5）外购数据集评估，100%；
|
||||
|
||||
2、算法开发
|
||||
|
||||
2.1) yolov11算法 的环境搭建，测试，训练完成 ，下一步将其移植到AILIB2框架优化现有算法。100%
|
||||
2.2）公路违停算法优化：标注车道线数据集并训练，已完成 ，下一步测试算法效果。80%
|
||||
|
||||
3、DSP优化：
|
||||
3.1）自测功能中，下周完成转测 ，70%。
|
||||
|
||||
|
||||
|
||||
|
||||
[2025-11-14 11:28:16] 执行命令: train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
[2025-11-14 11:28:16] 完整命令: cd /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics && echo '===== 训练任务信息 =====' > 003_CarRoadLane_N_1114-1100.log && echo '运行名称: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo '训练时间: $(date)' >> 003_CarRoadLane_N_1114-1100.log && echo 'YOLO版本: yolo11' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo 'project_path: /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics' >> 003_CarRoadLane_N_1114-1100.log && echo 'data_file: /home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml' >> 003_CarRoadLane_N_1114-1100.log && echo 'model_file: /home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt' >> 003_CarRoadLane_N_1114-1100.log && echo 'epochs: 220' >> 003_CarRoadLane_N_1114-1100.log && echo 'batch_size: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'img_size: 1280' >> 003_CarRoadLane_N_1114-1100.log && echo 'workers: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'device: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'project: 003_CarRoadLane' >> 003_CarRoadLane_N_1114-1100.log && echo 'name: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo 'exist_ok: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'resume: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'optimizer: SGD' >> 003_CarRoadLane_N_1114-1100.log && echo 'lr0: 0.01' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo '===== 开始训练 =====' >> 003_CarRoadLane_N_1114-1100.log && CUDA_VISIBLE_DEVICES=0 nohup /home/thsw2/miniconda3/envs/jcq_yolo11/bin/yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01 >> 003_CarRoadLane_N_1114-1100.log 2>&1 & echo $!
|
||||
[2025-11-14 11:28:34] 输出: 994531
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
|
||||
|
||||
|
||||
2025.10.13-2025.10.17
|
||||
|
||||
1、项目支撑
|
||||
|
||||
1.1）边缘计算项目评估支撑 -- 提供算法，确定提供算法模型，100%；
|
||||
1.2）陕西交控算法训练 ，待提供素材；
|
||||
1.3）水利标书文件算法部分补充，100%；
|
||||
1.4）溧宁高速算法优化，已确定问题，待排期处理。
|
||||
1.5）外购数据集评估，100%；
|
||||
|
||||
2、算法开发
|
||||
|
||||
2.1) yolov11算法 的环境搭建，测试，训练完成 ，下一步将其移植到AILIB2框架优化现有算法。100%
|
||||
2.2）公路违停算法优化：标注车道线数据集并训练，已完成 ，下一步测试算法效果。80%
|
||||
|
||||
3、DSP优化：
|
||||
3.1）自测功能中，下周完成转测 ，70%。
|
||||
|
||||
|
||||
|
||||
|
||||
[2025-11-14 11:28:16] 执行命令: train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
[2025-11-14 11:28:16] 完整命令: cd /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics && echo '===== 训练任务信息 =====' > 003_CarRoadLane_N_1114-1100.log && echo '运行名称: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo '训练时间: $(date)' >> 003_CarRoadLane_N_1114-1100.log && echo 'YOLO版本: yolo11' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo 'project_path: /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics' >> 003_CarRoadLane_N_1114-1100.log && echo 'data_file: /home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml' >> 003_CarRoadLane_N_1114-1100.log && echo 'model_file: /home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt' >> 003_CarRoadLane_N_1114-1100.log && echo 'epochs: 220' >> 003_CarRoadLane_N_1114-1100.log && echo 'batch_size: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'img_size: 1280' >> 003_CarRoadLane_N_1114-1100.log && echo 'workers: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'device: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'project: 003_CarRoadLane' >> 003_CarRoadLane_N_1114-1100.log && echo 'name: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo 'exist_ok: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'resume: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'optimizer: SGD' >> 003_CarRoadLane_N_1114-1100.log && echo 'lr0: 0.01' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo '===== 开始训练 =====' >> 003_CarRoadLane_N_1114-1100.log && CUDA_VISIBLE_DEVICES=0 nohup /home/thsw2/miniconda3/envs/jcq_yolo11/bin/yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01 >> 003_CarRoadLane_N_1114-1100.log 2>&1 & echo $!
|
||||
[2025-11-14 11:28:34] 输出: 994531
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
|
||||
|
||||
|
||||
2025.10.13-2025.10.17
|
||||
|
||||
1、项目支撑
|
||||
|
||||
1.1）边缘计算项目评估支撑 -- 提供算法，确定提供算法模型，100%；
|
||||
1.2）陕西交控算法训练 ，待提供素材；
|
||||
1.3）水利标书文件算法部分补充，100%；
|
||||
1.4）溧宁高速算法优化，已确定问题，待排期处理。
|
||||
1.5）外购数据集评估，100%；
|
||||
|
||||
2、算法开发
|
||||
|
||||
2.1) yolov11算法 的环境搭建，测试，训练完成 ，下一步将其移植到AILIB2框架优化现有算法。100%
|
||||
2.2）公路违停算法优化：标注车道线数据集并训练，已完成 ，下一步测试算法效果。80%
|
||||
|
||||
3、DSP优化：
|
||||
3.1）自测功能中，下周完成转测 ，70%。
|
||||
|
||||
|
||||
|
||||
|
||||
[2025-11-14 11:28:16] 执行命令: train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
[2025-11-14 11:28:16] 完整命令: cd /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics && echo '===== 训练任务信息 =====' > 003_CarRoadLane_N_1114-1100.log && echo '运行名称: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo '训练时间: $(date)' >> 003_CarRoadLane_N_1114-1100.log && echo 'YOLO版本: yolo11' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo 'project_path: /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics' >> 003_CarRoadLane_N_1114-1100.log && echo 'data_file: /home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml' >> 003_CarRoadLane_N_1114-1100.log && echo 'model_file: /home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt' >> 003_CarRoadLane_N_1114-1100.log && echo 'epochs: 220' >> 003_CarRoadLane_N_1114-1100.log && echo 'batch_size: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'img_size: 1280' >> 003_CarRoadLane_N_1114-1100.log && echo 'workers: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'device: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'project: 003_CarRoadLane' >> 003_CarRoadLane_N_1114-1100.log && echo 'name: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo 'exist_ok: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'resume: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'optimizer: SGD' >> 003_CarRoadLane_N_1114-1100.log && echo 'lr0: 0.01' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo '===== 开始训练 =====' >> 003_CarRoadLane_N_1114-1100.log && CUDA_VISIBLE_DEVICES=0 nohup /home/thsw2/miniconda3/envs/jcq_yolo11/bin/yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01 >> 003_CarRoadLane_N_1114-1100.log 2>&1 & echo $!
|
||||
[2025-11-14 11:28:34] 输出: 994531
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
Binary file not shown.
Binary file not shown.
|
|
@ -0,0 +1,40 @@
|
|||
|
||||
|
||||
|
||||
2025.10.13-2025.10.17
|
||||
|
||||
1、项目支撑
|
||||
|
||||
1.1）边缘计算项目评估支撑 -- 提供算法，确定提供算法模型，100%；
|
||||
1.2）陕西交控算法训练 ，待提供素材；
|
||||
1.3）水利标书文件算法部分补充，100%；
|
||||
1.4）溧宁高速算法优化，已确定问题，待排期处理。
|
||||
1.5）外购数据集评估，100%；
|
||||
|
||||
2、算法开发
|
||||
|
||||
2.1) yolov11算法 的环境搭建，测试，训练完成 ，下一步将其移植到AILIB2框架优化现有算法。100%
|
||||
2.2）公路违停算法优化：标注车道线数据集并训练，已完成 ，下一步测试算法效果。80%
|
||||
|
||||
3、DSP优化：
|
||||
3.1）自测功能中，下周完成转测 ，70%。
|
||||
|
||||
|
||||
|
||||
|
||||
[2025-11-14 11:28:16] 执行命令: train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
[2025-11-14 11:28:16] 完整命令: cd /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics && echo '===== 训练任务信息 =====' > 003_CarRoadLane_N_1114-1100.log && echo '运行名称: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo '训练时间: $(date)' >> 003_CarRoadLane_N_1114-1100.log && echo 'YOLO版本: yolo11' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo 'project_path: /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics' >> 003_CarRoadLane_N_1114-1100.log && echo 'data_file: /home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml' >> 003_CarRoadLane_N_1114-1100.log && echo 'model_file: /home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt' >> 003_CarRoadLane_N_1114-1100.log && echo 'epochs: 220' >> 003_CarRoadLane_N_1114-1100.log && echo 'batch_size: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'img_size: 1280' >> 003_CarRoadLane_N_1114-1100.log && echo 'workers: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'device: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'project: 003_CarRoadLane' >> 003_CarRoadLane_N_1114-1100.log && echo 'name: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo 'exist_ok: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'resume: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'optimizer: SGD' >> 003_CarRoadLane_N_1114-1100.log && echo 'lr0: 0.01' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo '===== 开始训练 =====' >> 003_CarRoadLane_N_1114-1100.log && CUDA_VISIBLE_DEVICES=0 nohup /home/thsw2/miniconda3/envs/jcq_yolo11/bin/yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01 >> 003_CarRoadLane_N_1114-1100.log 2>&1 & echo $!
|
||||
[2025-11-14 11:28:34] 输出: 994531
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
|
@ -0,0 +1,40 @@
|
|||
|
||||
|
||||
|
||||
2025.10.13-2025.10.17
|
||||
|
||||
1、项目支撑
|
||||
|
||||
1.1）边缘计算项目评估支撑 -- 提供算法，确定提供算法模型，100%；
|
||||
1.2）陕西交控算法训练 ，待提供素材；
|
||||
1.3）水利标书文件算法部分补充，100%；
|
||||
1.4）溧宁高速算法优化，已确定问题，待排期处理。
|
||||
1.5）外购数据集评估，100%；
|
||||
|
||||
2、算法开发
|
||||
|
||||
2.1) yolov11算法 的环境搭建，测试，训练完成 ，下一步将其移植到AILIB2框架优化现有算法。100%
|
||||
2.2）公路违停算法优化：标注车道线数据集并训练，已完成 ，下一步测试算法效果。80%
|
||||
|
||||
3、DSP优化：
|
||||
3.1）自测功能中，下周完成转测 ，70%。
|
||||
|
||||
|
||||
|
||||
|
||||
[2025-11-14 11:28:16] 执行命令: train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
[2025-11-14 11:28:16] 完整命令: cd /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics && echo '===== 训练任务信息 =====' > 003_CarRoadLane_N_1114-1100.log && echo '运行名称: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo '训练时间: $(date)' >> 003_CarRoadLane_N_1114-1100.log && echo 'YOLO版本: yolo11' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo 'project_path: /home/thsw2/jcq/projects/yolov11/ultralytics-main/ultralytics' >> 003_CarRoadLane_N_1114-1100.log && echo 'data_file: /home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml' >> 003_CarRoadLane_N_1114-1100.log && echo 'model_file: /home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt' >> 003_CarRoadLane_N_1114-1100.log && echo 'epochs: 220' >> 003_CarRoadLane_N_1114-1100.log && echo 'batch_size: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'img_size: 1280' >> 003_CarRoadLane_N_1114-1100.log && echo 'workers: 4' >> 003_CarRoadLane_N_1114-1100.log && echo 'device: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'project: 003_CarRoadLane' >> 003_CarRoadLane_N_1114-1100.log && echo 'name: 003_CarRoadLane_N_1114-1100' >> 003_CarRoadLane_N_1114-1100.log && echo 'exist_ok: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'resume: False' >> 003_CarRoadLane_N_1114-1100.log && echo 'optimizer: SGD' >> 003_CarRoadLane_N_1114-1100.log && echo 'lr0: 0.01' >> 003_CarRoadLane_N_1114-1100.log && echo '' >> 003_CarRoadLane_N_1114-1100.log && echo '===== 开始训练 =====' >> 003_CarRoadLane_N_1114-1100.log && CUDA_VISIBLE_DEVICES=0 nohup /home/thsw2/miniconda3/envs/jcq_yolo11/bin/yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01 >> 003_CarRoadLane_N_1114-1100.log 2>&1 & echo $!
|
||||
[2025-11-14 11:28:34] 输出: 994531
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
yolo train data=/home/thsw2/jcq/projects/yolov11/tuohengTraintask/Datasets/jcq/003_CarRoadLane.yaml model=/home/thsw2/jcq/projects/yolov11/weights/yolo11n.pt epochs=220 batch=4 imgsz=1280 workers=4 project=003_CarRoadLane name=003_CarRoadLane_N_1114-1100 optimizer=SGD lr0=0.01
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
File diff suppressed because it is too large
Load Diff
|
|
@ -1,17 +0,0 @@
|
|||
services:
|
||||
db:
|
||||
image: pgvector/pgvector:pg16
|
||||
container_name: pgvector-db
|
||||
environment:
|
||||
POSTGRES_USER: drgraph
|
||||
POSTGRES_PASSWORD: yingping
|
||||
POSTGRES_DB: th_agenter
|
||||
ports:
|
||||
- "5432:5432"
|
||||
volumes:
|
||||
- pgdata:/var/lib/postgresql/data
|
||||
restart: unless-stopped
|
||||
|
||||
volumes:
|
||||
pgdata:
|
||||
# docker exec -it pgvector-db psql -U drgraph -d th_agenter
|
||||
131
backend/main.py
131
backend/main.py
|
|
@ -1,131 +0,0 @@
|
|||
# uvicorn main:app --host 0.0.0.0 --port 8000 --reload
|
||||
from fastapi import FastAPI
|
||||
from os.path import dirname, realpath
|
||||
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv()
|
||||
|
||||
from utils.util_log import init_logger
|
||||
from loguru import logger
|
||||
base_dir: str = dirname(realpath(__file__))
|
||||
init_logger(base_dir)
|
||||
|
||||
from th_agenter.api.routes import router
|
||||
from contextlib import asynccontextmanager
|
||||
from starlette.exceptions import HTTPException as StarletteHTTPException
|
||||
from fastapi.exceptions import RequestValidationError
|
||||
from fastapi.responses import JSONResponse
|
||||
from fastapi.staticfiles import StaticFiles
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
"""Application lifespan manager."""
|
||||
logger.info("[生命周期] - Starting up TH Agenter application...")
|
||||
yield
|
||||
# Shutdown
|
||||
logger.info("[生命周期] - Shutting down TH Agenter application...")
|
||||
|
||||
def setup_exception_handlers(app: FastAPI) -> None:
|
||||
"""Setup global exception handlers."""
|
||||
|
||||
# Import custom exceptions and handlers
|
||||
from utils.util_exceptions import ChatAgentException, chat_agent_exception_handler
|
||||
|
||||
@app.exception_handler(ChatAgentException)
|
||||
async def custom_chat_agent_exception_handler(request, exc):
|
||||
return await chat_agent_exception_handler(request, exc)
|
||||
|
||||
@app.exception_handler(StarletteHTTPException)
|
||||
async def http_exception_handler(request, exc):
|
||||
from utils.util_exceptions import HxfErrorResponse
|
||||
logger.exception(f"HTTP Exception: {exc.status_code} - {exc.detail} - {request.method} {request.url}")
|
||||
return HxfErrorResponse(exc)
|
||||
|
||||
def make_json_serializable(obj):
|
||||
"""递归地将对象转换为JSON可序列化的格式"""
|
||||
if obj is None or isinstance(obj, (str, int, float, bool)):
|
||||
return obj
|
||||
elif isinstance(obj, bytes):
|
||||
return obj.decode('utf-8')
|
||||
elif isinstance(obj, (ValueError, Exception)):
|
||||
return str(obj)
|
||||
elif isinstance(obj, dict):
|
||||
return {k: make_json_serializable(v) for k, v in obj.items()}
|
||||
elif isinstance(obj, (list, tuple)):
|
||||
return [make_json_serializable(item) for item in obj]
|
||||
else:
|
||||
# For any other object, convert to string
|
||||
return str(obj)
|
||||
|
||||
@app.exception_handler(RequestValidationError)
|
||||
async def validation_exception_handler(request, exc):
|
||||
# Convert any non-serializable objects to strings in error details
|
||||
try:
|
||||
errors = make_json_serializable(exc.errors())
|
||||
except Exception as e:
|
||||
# Fallback: if even our conversion fails, use a simple error message
|
||||
errors = [{"type": "serialization_error", "msg": f"Error processing validation details: {str(e)}"}]
|
||||
logger.exception(f"Request Validation Error: {errors}")
|
||||
|
||||
logger.exception(f"validation_error: {errors}")
|
||||
return JSONResponse(
|
||||
status_code=422,
|
||||
content={
|
||||
"error": {
|
||||
"type": "validation_error",
|
||||
"message": "Request validation failed",
|
||||
"details": errors
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
@app.exception_handler(Exception)
|
||||
async def general_exception_handler(request, exc):
|
||||
logger.error(f"Unhandled exception: {exc}", exc_info=True)
|
||||
return JSONResponse(
|
||||
status_code=500,
|
||||
content={
|
||||
"error": {
|
||||
"type": "internal_error",
|
||||
"message": "Internal server error"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
def create_app() -> FastAPI:
|
||||
"""Create and configure FastAPI application."""
|
||||
from th_agenter.core.config import get_settings
|
||||
settings = get_settings()
|
||||
|
||||
# Create FastAPI app
|
||||
app = FastAPI(
|
||||
title=settings.app_name,
|
||||
version=settings.app_version,
|
||||
description="基于Vue的第一个聊天智能体应用，使用FastAPI后端，由TH Agenter修改",
|
||||
debug=settings.debug,
|
||||
lifespan=lifespan,
|
||||
)
|
||||
app.mount("/static", StaticFiles(directory="static"), name="th_agenter_static")
|
||||
|
||||
# Add middleware
|
||||
from th_agenter.core.app import setup_middleware
|
||||
setup_middleware(app, settings)
|
||||
|
||||
# # Add exception handlers
|
||||
setup_exception_handlers(app)
|
||||
add_router(app)
|
||||
|
||||
return app
|
||||
|
||||
def add_router(app: FastAPI) -> None:
|
||||
"""Add default routers to the FastAPI application."""
|
||||
|
||||
@app.get("/")
|
||||
def read_root():
|
||||
logger.info("Hello World")
|
||||
return {"Hello": "World"}
|
||||
|
||||
# Include routers
|
||||
app.include_router(router, prefix="/api")
|
||||
|
||||
app = create_app()
|
||||
# from test.example import internet_search_tool
|
||||
Binary file not shown.
|
Before Width: | Height: | Size: 4.9 KiB |
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
|
|
@ -1 +0,0 @@
|
|||
# Test package for PostgreSQL agent functionality
|
||||
|
|
@ -1,154 +0,0 @@
|
|||
import os
|
||||
import asyncio
|
||||
from datetime import datetime
|
||||
from deepagents import create_deep_agent
|
||||
from openai import OpenAI
|
||||
from langchain.chat_models import init_chat_model
|
||||
from langchain.agents import create_agent
|
||||
from langgraph.checkpoint.memory import InMemorySaver, MemorySaver # 导入检查点工具
|
||||
from deepagents.backends import StoreBackend
|
||||
from loguru import logger
|
||||
def internet_search_tool(query: str):
|
||||
"""Run a web search"""
|
||||
logger.info(f"Running internet search for query: {query}")
|
||||
client = OpenAI(
|
||||
api_key=os.getenv('DASHSCOPE_API_KEY'),
|
||||
base_url=os.getenv('DASHSCOPE_BASE_URL'),
|
||||
)
|
||||
logger.info(f"create OpenAI")
|
||||
completion = client.chat.completions.create(
|
||||
model="qwen-plus",
|
||||
messages=[
|
||||
{'role': 'system', 'content': 'You are a helpful assistant.'},
|
||||
{'role': 'user', 'content': query}
|
||||
],
|
||||
extra_body={
|
||||
"enable_search": True
|
||||
}
|
||||
)
|
||||
logger.info(f"create completions")
|
||||
logger.info(f"OpenAI response: {completion.choices[0].message.content}")
|
||||
return completion.choices[0].message.content
|
||||
|
||||
|
||||
|
||||
# System prompt to steer the agent to be an expert researcher
|
||||
today = datetime.now().strftime("%Y年%m月%d日")
|
||||
research_instructions = f"""你是一个智能助手。你的任务是帮助用户完成各种任务。
|
||||
|
||||
你可以使用互联网搜索工具来获取信息。
|
||||
## `internet_search`
|
||||
使用此工具对给定查询进行互联网搜索。你可以指定返回结果的最大数量、主题以及是否包含原始内容。
|
||||
|
||||
今天的日期是：{today}
|
||||
"""
|
||||
|
||||
# Create the deep agent with memory
|
||||
model = init_chat_model(
|
||||
model="gpt-4.1-mini",
|
||||
model_provider='openai',
|
||||
api_key=os.getenv('OPENAI_API_KEY'),
|
||||
base_url=os.getenv('OPENAI_BASE_URL'),
|
||||
)
|
||||
checkpointer = InMemorySaver() # 创建内存检查点，自动保存历史
|
||||
|
||||
agent = create_deep_agent( # state：thread会话级的状态
|
||||
tools=[internet_search_tool],
|
||||
system_prompt=research_instructions,
|
||||
model=model,
|
||||
checkpointer=checkpointer, # 添加检查点，启用自动记忆
|
||||
interrupt_on={'internet_search_tool':True}
|
||||
)
|
||||
|
||||
# 多轮对话循环（使用 Checkpointer 自动记忆）
|
||||
printed_msg_ids = set() # 跟踪已打印的消息ID
|
||||
thread_id = "user_session_001" # 会话 ID，区分不同用户/会话
|
||||
config = {"configurable": {"thread_id": thread_id}, "metastore": {'assistant_id': 'owenliang'}} # 配置会话
|
||||
|
||||
print("开始对话（输入 'exit' 退出）：")
|
||||
while True:
|
||||
user_input = input("\nHUMAN: ").strip()
|
||||
if user_input.lower() == 'exit':
|
||||
break
|
||||
|
||||
# 使用 values 模式多次返回完整状态，这里按 message.id 去重，并按类型分类打印
|
||||
pending_resume = None
|
||||
while True:
|
||||
if pending_resume is None:
|
||||
request = {"messages": [{"role": "user", "content": user_input}]}
|
||||
else:
|
||||
from langgraph.types import Command as _Command
|
||||
|
||||
request = _Command(resume=pending_resume)
|
||||
pending_resume = None
|
||||
|
||||
for item in agent.stream(
|
||||
request,
|
||||
config=config,
|
||||
stream_mode="values",
|
||||
):
|
||||
state = item[0] if isinstance(item, tuple) and len(item) == 2 else item
|
||||
|
||||
# 先检查是否触发了 Human-In-The-Loop 中断
|
||||
if isinstance(state, dict) and "__interrupt__" in state:
|
||||
interrupts = state["__interrupt__"] or []
|
||||
if interrupts:
|
||||
hitl_payload = interrupts[0].value
|
||||
action_requests = hitl_payload.get("action_requests", [])
|
||||
|
||||
print("\n=== 需要人工审批的工具调用 ===")
|
||||
decisions: list[dict[str, str]] = []
|
||||
for idx, ar in enumerate(action_requests):
|
||||
name = ar.get("name")
|
||||
args = ar.get("args")
|
||||
print(f"[{idx}] 工具 {name} 参数: {args}")
|
||||
while True:
|
||||
choice = input(" 决策 (a=approve, r=reject): ").strip().lower()
|
||||
if choice in ("a", "r"):
|
||||
break
|
||||
decisions.append({"type": "approve" if choice == "a" else "reject"})
|
||||
|
||||
# 下一轮调用改为 resume，同一轮用户回合继续往下跑
|
||||
pending_resume = {"decisions": decisions}
|
||||
break
|
||||
|
||||
# 兼容 dict state 和 AgentState dataclass
|
||||
messages = state.get("messages", []) if isinstance(state, dict) else getattr(state, "messages", [])
|
||||
for msg in messages:
|
||||
msg_id = getattr(msg, "id", None)
|
||||
if msg_id is not None and msg_id in printed_msg_ids:
|
||||
continue
|
||||
if msg_id is not None:
|
||||
printed_msg_ids.add(msg_id)
|
||||
|
||||
msg_type = getattr(msg, "type", None)
|
||||
|
||||
if msg_type == "human":
|
||||
# 用户输入已经在命令行里，不再重复打印
|
||||
continue
|
||||
|
||||
if msg_type == "ai":
|
||||
tool_calls = getattr(msg, "tool_calls", None) or []
|
||||
if tool_calls:
|
||||
# 这是发起工具调用的 AI 消息（TOOL CALL）
|
||||
for tc in tool_calls:
|
||||
tool_name = tc.get("name")
|
||||
args = tc.get("args")
|
||||
print(f"TOOL CALL [{tool_name}]: {args}")
|
||||
# 如果 AI 同时带有自然语言内容，也一起打印
|
||||
if getattr(msg, "content", None):
|
||||
print(f"AI: {msg.content}")
|
||||
continue
|
||||
|
||||
if msg_type == "tool":
|
||||
# 工具执行结果（TOOL RESPONSE）
|
||||
tool_name = getattr(msg, "name", None) or "tool"
|
||||
print(f"TOOL RESPONSE [{tool_name}]: {msg.content}")
|
||||
continue
|
||||
|
||||
# 兜底：其它类型直接打印出来便于调试
|
||||
print(f"[{msg_type}]: {getattr(msg, 'content', None)}")
|
||||
|
||||
# 如果没有新的中断需要 resume，则整轮结束，等待下一轮用户输入
|
||||
if pending_resume is None:
|
||||
break
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
|
@ -1 +1 @@
|
|||
"""API module for TH Agenter."""
|
||||
"""API module for TH-Agenter."""
|
||||
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
|
|
@ -1 +1 @@
|
|||
"""API endpoints for TH Agenter."""
|
||||
"""API endpoints for TH-Agenter."""
|
||||
Binary file not shown.
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue